{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FE2DO23FIJQPO5I2PAU7TZQCCE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"974cfef84ef9bd1eb0803b62d26435219f95145844cc872d7f4950bf2cfb5e30","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-23T16:51:09Z","title_canon_sha256":"f5ee28d623ee14158ebaaf055a829c80cb04fb56c22fa6628ea31dcbb0f86ade"},"schema_version":"1.0","source":{"id":"2507.17686","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.17686","created_at":"2026-07-05T12:03:50Z"},{"alias_kind":"arxiv_version","alias_value":"2507.17686v3","created_at":"2026-07-05T12:03:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.17686","created_at":"2026-07-05T12:03:50Z"},{"alias_kind":"pith_short_12","alias_value":"FE2DO23FIJQP","created_at":"2026-07-05T12:03:50Z"},{"alias_kind":"pith_short_16","alias_value":"FE2DO23FIJQPO5I2","created_at":"2026-07-05T12:03:50Z"},{"alias_kind":"pith_short_8","alias_value":"FE2DO23F","created_at":"2026-07-05T12:03:50Z"}],"graph_snapshots":[{"event_id":"sha256:5f97f4887dd0bec53015be92af9c6fbf43a060c4557338fe09b017f7dff50d22","target":"graph","created_at":"2026-07-05T12:03:50Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.17686/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Previous studies have shown that hazard ratios between treatment groups estimated with the Cox model are uninterpretable because the unspecified baseline hazard of the model fails to identify temporal change in the risk set composition due to treatment assignment and unobserved factors among multiple, contradictory scenarios. To alleviate this problem, especially in studies based on observational data with uncontrolled dynamic treatment and real-time measurement of many covariates, we propose abandoning the baseline hazard and using kernel-based machine learning to explicitly model the change ","authors_text":"Satoshi Asai, Takashi Hayakawa","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-23T16:51:09Z","title":"Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.17686","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:768aa9fb1cf67673dd25184d1745f1231776ee3bf194540aa401f36fe1d6e7e7","target":"record","created_at":"2026-07-05T12:03:50Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"974cfef84ef9bd1eb0803b62d26435219f95145844cc872d7f4950bf2cfb5e30","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-23T16:51:09Z","title_canon_sha256":"f5ee28d623ee14158ebaaf055a829c80cb04fb56c22fa6628ea31dcbb0f86ade"},"schema_version":"1.0","source":{"id":"2507.17686","kind":"arxiv","version":3}},"canonical_sha256":"2934376b654260f7751a7829f9e602111d50747dee9adfb28c2e42e58b8b94c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2934376b654260f7751a7829f9e602111d50747dee9adfb28c2e42e58b8b94c9","first_computed_at":"2026-07-05T12:03:50.177541Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:50.177541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cdvMT2dXbEgzjFRgUN75aUw2J53fmbxSpIKwJArzQ7/z1t3cOe25Vuh8NDN2llKLgCj6Sl4QS4Hi9MxzzkWLBw==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:50.178349Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.17686","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:768aa9fb1cf67673dd25184d1745f1231776ee3bf194540aa401f36fe1d6e7e7","sha256:5f97f4887dd0bec53015be92af9c6fbf43a060c4557338fe09b017f7dff50d22"],"state_sha256":"053cd015fc554ffe500dd03a88807fccfdf18426cb1bd4e94e668e732742834e"}